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In sequential recommendation (SR), system exposure refers to items that are exposed to the user.
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Xiaojie Wang, Rui Zhang, Yu Sun, and Jianzhong Qi. 2019 · 2019
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A Simple Convolutional Generative Network for Next Item Recommendation. In WSDM . ACM, 582–590
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Morel: Model-based offline reinforcement learning
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Conservative q-learning for offline reinforcement learning
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A general knowledge distillation framework for counterfactual recommendation via uniform data. In Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval . 831–840
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KuaiRand: An Unbiased Sequential Recommendation Dataset with Randomly Exposed Videos. In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (Atlanta, GA, USA) (CIKM ’22) . 3953–3957
Chongming Gao, Shijun Li, Yuan Zhang, Jiawei Chen, Biao Li, Wenqiang Lei, Peng Jiang, and Xiangnan He. 2022 · 2022
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Core: simple and effective session-based recommendation within consistent representation space. In Proceedings of the 45th international ACM SIGIR conference on research and development in information retrieval . 1796–1801
Yupeng Hou, Binbin Hu, Zhiqiang Zhang, and Wayne Xin Zhao. 2022 · 2022
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Rambo-rl: Robust adversarial model-based offline reinforcement learning
Marc Rigter, Bruno Lacerda, and Nick Hawes. 2022 · 2022
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Dually Enhanced Propensity Score Estimation in Sequential Recommendation. In CIKM . 2260–2269
Chen Xu, Jun Xu, Xu Chen, Zhenghua Dong, and Ji-Rong Wen. 2022 · 2022
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Tenrec: A large-scale multipurpose benchmark dataset for recommender systems
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Model-Based Offline Planning with Trajectory Pruning
Xianyuan Zhan, Xiangyu Zhu, and Haoran Xu. 2022 · 2022
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Bias and debias in recommender system: A survey and future directions
Jiawei Chen, Hande Dong, Xiang Wang, Fuli Feng, Meng Wang, and Xiangnan He. 2023a · 2023
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Deep reinforcement learning in recommender systems: A survey and new perspectives
Xiaocong Chen, Lina Yao, Julian McAuley, Guanglin Zhou, and Xianzhi Wang. 2023b · 2023
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Frequency enhanced hybrid attention network for sequential recommendation. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval . 78–88
Xinyu Du, Huanhuan Yuan, Pengpeng Zhao, Jianfeng Qu, Fuzhen Zhuang, Guanfeng Liu, Yanchi Liu, and Victor S Sheng. 2023 · 2023
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Bounding System-Induced Biases in Recommender Systems with a Randomized Dataset
Dugang Liu, Pengxiang Cheng, Zinan Lin, Xiaolian Zhang, Zhenhua Dong, Rui Zhang, Xiuqiang He, Weike Pan, and Zhong Ming. 2023 · 2023
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Impression-Aware Recommender Systems
Fernando B Pérez Maurera, Maurizio Ferrari Dacrema, Pablo Castells, and Paolo Cremonesi. 2023 · 2023
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User Simulation for Evaluating Information Access Systems
Krisztian Balog and ChengXiang Zhai. 2024 · 2024
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Sequential Recommendation for Optimizing Both Immediate Feedback and Long-term Retention. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval . 1872–1882
Ziru Liu, Shuchang Liu, Zijian Zhang, Qingpeng Cai, Xiangyu Zhao, Kesen Zhao, Lantao Hu, Peng Jiang, and Kun Gai. 2024 · 2024
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Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Exposure. In Proceedings of the 17th ACM International Conference on Web Search and Data Mining . 882–890
Jiyuan Yang, Yue Ding, Yidan Wang, Pengjie Ren, Zhumin Chen, Fei Cai, Jun Ma, Rui Zhang, Zhaochun Ren, and Xin Xin. 2024 · 2024
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Off-policy deep reinforcement learning without exploration. In International conference on machine learning . PMLR, 2052–2062
Scott Fujimoto, David Meger, and Doina Precup. 2019 · 2062
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